Optimal trading mechanism for prosumer-centric local energy markets considering deviation assessment

Local energy markets with integrated distributed power prosumers who can produce and consume renewable energy are gradually becoming prosperous with the acceleration of the carbon neutrality process. It is crucial to explore optimal trading mechanism for prosumer-centric local energy markets considering deviation assessment due to the volatility of renewable energy. This study proposed a novel distributed power agency trading (DPAT) mechanism considering deviation assessment based on dynamic game theory, which is formulated by adopting a bilevel Stackelberg model whereby prosumers at lower levels optimize both electricity consumption and pricing strategies considering their expectations of the trading price. Specifically, when the purchase price offered by an agent is higher than the price the prosumer expected, the latter, as a buyer, will select the external market direct trading (EMDT) value. The subgame Nash equilibrium can be derived by nonlinear optimization theory, which demonstrates that prosumer equilibrium price equal to the agent, but equilibrium consumption strategies decrease linearly with aggregator and external market prices, where the former increases linearly with the latter. Furthermore, to explore prosumer' mechanism selection preference at different times in the day when considering deviation assessment, this study conducted simulations based on actual data from the spot market. The results show that prosumers prefer the DPAT mechanism during peak load hours at noon and the EMDT mechanism during other periods of operation. Additionally, prosumers prefer the DPAT mechanism from the perspective of environmental benefits as it provides more than 8.8% carbon reduction compared to EMDT. This study can guide local energy market to establish optimal trading mechanisms and prosumers to develop optimal trading strategies, and promote achievement of regional carbon neutrality goals.

Automated summary

This study proposes a distributed power agency trading mechanism based on dynamic game theory and deviation assessment for local energy markets with integrated distributed power prosumers. Simulation results show that prosumers prefer this mechanism during peak load hours at noon and it provides higher carbon reduction compared to other mechanisms.